ray-skill

Use when user says "send to Ray," "show in Ray," "debug in Ray," "log to Ray," "display in Ray," or wants to visualize data, debug output, or show diagrams in the Ray desktop application.

Quality

63%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./config/claude/skills/ray-skill/SKILL.md

Quality

Discovery

62%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description excels at trigger term coverage and distinctiveness by clearly anchoring to the Ray desktop application with multiple natural user phrases. However, it critically lacks a 'what does this do' component — there are no concrete capability statements explaining what actions the skill performs. This makes it a strong trigger-matching description but an incomplete skill description overall.

Suggestions

Add a capability statement before the 'Use when' clause, e.g., 'Sends data, variables, debug output, and diagrams to the Ray desktop application for visualization and debugging.'

List specific concrete actions the skill performs, such as 'log variables, display collections, render diagrams, show query results, send exception traces to Ray.'

Dimension	Reasoning	Score
Specificity	The description lacks concrete actions describing what the skill actually does. It mentions 'visualize data, debug output, or show diagrams' but these are vague and appear only in the trigger clause, not as explicit capability statements. There is no 'what does this do' section listing specific actions.	1 / 3
Completeness	The 'when' is very well covered with explicit trigger phrases, but the 'what' is essentially missing. The description never explains what the skill concretely does — e.g., does it send data via an API, generate Ray-compatible code, format output? The what is only vaguely implied through the trigger terms.	2 / 3
Trigger Term Quality	Excellent coverage of natural trigger phrases users would say: 'send to Ray,' 'show in Ray,' 'debug in Ray,' 'log to Ray,' 'display in Ray,' plus broader terms like 'visualize data,' 'debug output,' and 'show diagrams.' These are highly natural and varied.	3 / 3
Distinctiveness Conflict Risk	The repeated mention of 'Ray' as a specific desktop application creates a very clear niche. The trigger phrases are all anchored to 'Ray,' making it highly unlikely to conflict with other debugging or visualization skills.	3 / 3
	Total	9 / 12 Passed

Implementation

64%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a solid API reference skill with excellent actionability—every payload type has a concrete, executable JSON example and there's a complete curl command. However, it suffers from significant repetition (the origin object appears identically in every example) and could be more concise by showing the origin once and abbreviating it in subsequent examples. The workflow could be improved with explicit sequencing (check availability → send → handle errors).

Suggestions

Show the origin object once in full, then use a shorthand like `"origin": { ... }` in subsequent payload examples to dramatically reduce repetition and token usage.

Add an explicit workflow sequence: 1) Check availability via GET, 2) Send payload via POST, 3) Handle connection errors (Ray not running), to improve workflow clarity.

Consider splitting the detailed payload type examples into a separate PAYLOAD_TYPES.md reference file, keeping only the most common types (log, custom, table, color) in the main skill.

Dimension	Reasoning	Score
Conciseness	The content is fairly efficient as an API reference but has significant redundancy: the origin object is repeated verbatim in every single payload example (12+ times), and the payload type reference table at the end duplicates information already shown in detail above. The 'Origin Object' section explains something that's already clear from the examples.	2 / 3
Actionability	Highly actionable with complete, copy-paste ready JSON payloads and a full curl command example. Every payload type has a concrete, executable example with exact field names and values. The availability check endpoint is also specified precisely.	3 / 3
Workflow Clarity	The availability check is mentioned but not integrated into a clear workflow sequence (e.g., 'first check availability, then send'). The combining payloads section explains the UUID reuse pattern well, but there's no explicit guidance on error handling if Ray isn't running or if requests fail.	2 / 3
Progressive Disclosure	The content is a long monolithic document (~200+ lines) that could benefit from splitting the detailed payload type examples into a separate reference file. The structure uses headers well, but all content is inline with no references to supplementary files. The summary table at the end is helpful for quick reference but the detailed examples above it make the document quite long.	2 / 3
	Total	9 / 12 Passed

Validation

81%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
metadata_field	'metadata' should map string keys to string values	Warning

	Total	9 / 11 Passed

Repository: freekmurze/dotfiles
Commit: 05d40bb

Reviewed: 14 days ago

Table of Contents

Discovery Implementation Validation

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